It is not uncommon to see the data associated with a business venture grow at an exponential pace. Thus, a variety of techniques to compress large amounts of data have been developed to conserve storage resources. On the other hand, larger and less expensive disks have become increasingly available, as have multiple processors per node. Data compression has therefore also been used to enable keeping large amounts of data online, assisting with deep analysis and a reduction in input/output (I/O) cost. The existence and availability of various compression mechanisms, along with less expensive storage and processing, consequently pose a new challenge: how does a database administrator make intelligent choices among all the alternatives in an efficient manner?